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refactoring

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This commit is contained in:
Miha Kralj
2025-12-16 21:16:50 -08:00
parent a67ad65fa5
commit d277e08056
137 changed files with 5074 additions and 3178 deletions
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lib/trends/mama/Mama.Quantower.Tests.cs
+1 -1
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@@ -47,7 +47,7 @@ public class MamaIndicatorTests
indicator.Initialize();
// After init, line series should exist (MAMA and FAMA)
Assert.Equal(2, indicator.LinesSeries.Length);
Assert.Equal(2, indicator.LinesSeries.Count);
}
[Fact]
lib/trends/mama/Mama.Quantower.cs
+5 -5
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@@ -35,10 +35,10 @@ public class MamaIndicator : Indicator, IWatchlistIndicator
SourceName = Source.ToString();
Name = "MAMA - MESA Adaptive Moving Average";
Description = "MESA Adaptive Moving Average";
MamaSeries = new(name: "MAMA", color: Color.Red, width: 2, style: LineStyle.Solid);
FamaSeries = new(name: "FAMA", color: Color.Blue, width: 2, style: LineStyle.Solid);
AddLineSeries(MamaSeries);
AddLineSeries(FamaSeries);
}
@@ -55,12 +55,12 @@ public class MamaIndicator : Indicator, IWatchlistIndicator
{
TValue input = this.GetInputValue(args, Source);
bool isNew = args.Reason == UpdateReason.NewBar || args.Reason == UpdateReason.HistoricalBar;
TValue result = _ma!.Update(input, isNew);
MamaSeries!.SetValue(result.Value);
FamaSeries!.SetValue(_ma.Fama.Value);
MamaSeries!.SetMarker(0, Color.Transparent);
FamaSeries!.SetMarker(0, Color.Transparent);
lib/trends/mama/Mama.Tests.cs
+1 -1
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@@ -170,7 +170,7 @@ public class MamaTests
var mama = new Mama();
var series1 = mama.Update(source);
var series2 = Mama.Calculate(source);
var series2 = Mama.Batch(source);
Assert.Equal(series1.Count, series2.Count);
for (int i = 0; i < source.Count; i++)
lib/trends/mama/Mama.cs
+187 -20
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@@ -1,5 +1,7 @@
using System;
using System.Collections.Generic;
using System.Runtime.CompilerServices;
using System.Runtime.InteropServices;
namespace QuanTAlib;
@@ -8,12 +10,10 @@ namespace QuanTAlib;
/// A trend-following indicator that adapts to the market's phase rate of change.
/// </summary>
[SkipLocalsInit]
public sealed class Mama : ITValuePublisher
public sealed class Mama : AbstractBase
{
public TValue Last { get; private set; }
public TValue Fama { get; private set; }
public bool IsHot => _state.Index > 6;
public event Action<TValue>? Pub;
public override bool IsHot => _state.Index > 6;
private readonly double _fastLimit;
private readonly double _slowLimit;
@@ -52,6 +52,7 @@ public sealed class Mama : ITValuePublisher
_Q1_buffer = new RingBuffer(7);
Name = $"Mama({fastLimit:F2},{slowLimit:F2})";
WarmupPeriod = 7;
Init();
}
@@ -65,7 +66,7 @@ public sealed class Mama : ITValuePublisher
Reset();
}
public void Reset()
public override void Reset()
{
_state = default;
_state.Mama = double.NaN;
@@ -83,7 +84,7 @@ public sealed class Mama : ITValuePublisher
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public TValue Update(TValue input, bool isNew = true)
private double Step(double price, bool isNew)
{
if (isNew)
{
@@ -95,7 +96,6 @@ public sealed class Mama : ITValuePublisher
_state = _p_state;
}
double price = input.Value;
if (!double.IsFinite(price))
{
price = _state.LastValidPrice;
@@ -186,7 +186,7 @@ public sealed class Mama : ITValuePublisher
double avg = _state.Index > 0 ? _state.SumPr / _state.Index : price;
_state.Mama = avg;
_state.Fama = avg;
// Initialize buffers with 0
_smoothBuffer.Add(0, isNew);
_detrender.Add(0, isNew);
@@ -194,15 +194,22 @@ public sealed class Mama : ITValuePublisher
_Q1_buffer.Add(0, isNew);
}
Last = new TValue(input.Time, _state.Mama);
return _state.Mama;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public override TValue Update(TValue input, bool isNew = true)
{
double mama = Step(input.Value, isNew);
Last = new TValue(input.Time, mama);
Fama = new TValue(input.Time, _state.Fama);
Pub?.Invoke(Last);
PubEvent(Last);
return Last;
}
public TSeries Update(TSeries source)
public override TSeries Update(TSeries source)
{
if (source.Count == 0) return [];
if (source.Count == 0) return new TSeries([], []);
int len = source.Count;
var v = new List<double>(len);
@@ -210,16 +217,23 @@ public sealed class Mama : ITValuePublisher
for (int i = 0; i < len; i++)
{
var item = source[i];
var result = Update(item);
var result = Update(new TValue(source.Times[i], source.Values[i]));
t.Add(result.Time);
v.Add(result.Value);
t.Add(item.Time);
}
return new TSeries(t, v);
}
public static TSeries Calculate(TSeries source, double fastLimit = 0.5, double slowLimit = 0.05)
public override void Prime(ReadOnlySpan<double> source)
{
foreach (var value in source)
{
Step(value, true);
}
}
public static TSeries Batch(TSeries source, double fastLimit = 0.5, double slowLimit = 0.05)
{
var mama = new Mama(fastLimit, slowLimit);
return mama.Update(source);
@@ -227,12 +241,165 @@ public sealed class Mama : ITValuePublisher
public static void Calculate(ReadOnlySpan<double> source, Span<double> output, double fastLimit = 0.5, double slowLimit = 0.05)
{
var mama = new Mama(fastLimit, slowLimit);
if (source.Length == 0) return;
// Stack allocate buffers for high performance (size 8 for power of 2 masking)
// We need 7 elements, but 8 allows & 7 masking
Span<double> priceBuffer = stackalloc double[8];
Span<double> smoothBuffer = stackalloc double[8];
Span<double> detrender = stackalloc double[8];
Span<double> I1_buffer = stackalloc double[8];
Span<double> Q1_buffer = stackalloc double[8];
int bufferIdx = 0; // Current index for circular buffer
int count = 0;
// State variables
double period = 0, mama = 0, sumPr = 0;
double i2 = 0, q2 = 0, re = 0, im = 0, lastValidPrice = 0;
double p_period = 0, p_phase = 0, p_mama = 0;
double p_i2 = 0, p_q2 = 0, p_re = 0, p_im = 0;
// Constants
const int Mask = 7;
for (int i = 0; i < source.Length; i++)
{
output[i] = mama.Update(new TValue(DateTime.MinValue, source[i])).Value;
double price = source[i];
if (!double.IsFinite(price))
{
price = count > 0 ? lastValidPrice : 0.0;
}
else
{
lastValidPrice = price;
}
// Circular buffer update
bufferIdx = (bufferIdx + 1) & Mask;
priceBuffer[bufferIdx] = price;
count++;
if (count > 6)
{
double adj = (0.075 * period) + 0.54;
// Smooth
double smooth = (4.0 * priceBuffer[bufferIdx] +
3.0 * priceBuffer[(bufferIdx - 1) & Mask] +
2.0 * priceBuffer[(bufferIdx - 2) & Mask] +
priceBuffer[(bufferIdx - 3) & Mask]) * 0.1;
smoothBuffer[bufferIdx] = smooth;
// Detrender
double dt = (c1 * smoothBuffer[bufferIdx] +
c2 * smoothBuffer[(bufferIdx - 2) & Mask] -
c2 * smoothBuffer[(bufferIdx - 4) & Mask] -
c1 * smoothBuffer[(bufferIdx - 6) & Mask]) * adj;
detrender[bufferIdx] = dt;
// Q1
double q1 = (c1 * dt +
c2 * detrender[(bufferIdx - 2) & Mask] -
c2 * detrender[(bufferIdx - 4) & Mask] -
c1 * detrender[(bufferIdx - 6) & Mask]) * adj;
Q1_buffer[bufferIdx] = q1;
// I1 = dt[3]
double i1 = detrender[(bufferIdx - 3) & Mask];
I1_buffer[bufferIdx] = i1;
// Advance phases
double jI = (c1 * i1 +
c2 * I1_buffer[(bufferIdx - 2) & Mask] -
c2 * I1_buffer[(bufferIdx - 4) & Mask] -
c1 * I1_buffer[(bufferIdx - 6) & Mask]) * adj;
double jQ = (c1 * q1 +
c2 * Q1_buffer[(bufferIdx - 2) & Mask] -
c2 * Q1_buffer[(bufferIdx - 4) & Mask] -
c1 * Q1_buffer[(bufferIdx - 6) & Mask]) * adj;
// Phasor addition
double i2_val = i1 - jQ;
double q2_val = q1 + jI;
// Smooth i2, q2
i2 = 0.2 * i2_val + 0.8 * p_i2;
q2 = 0.2 * q2_val + 0.8 * p_q2;
// Homodyne discriminator
double re_val = (i2 * p_i2) + (q2 * p_q2);
double im_val = (i2 * p_q2) - (q2 * p_i2);
// Smooth re, im
re = 0.2 * re_val + 0.8 * p_re;
im = 0.2 * im_val + 0.8 * p_im;
// Calculate Period
double newPeriod = (Math.Abs(im) > double.Epsilon && Math.Abs(re) > double.Epsilon)
? TWOPI / Math.Atan(im / re)
: 0.0;
// Adjust Period
double periodCap = p_period * 1.5;
double periodFloor = p_period * 0.67;
if (newPeriod > periodCap) newPeriod = periodCap;
if (newPeriod < periodFloor) newPeriod = periodFloor;
if (newPeriod < 6.0) newPeriod = 6.0;
if (newPeriod > 50.0) newPeriod = 50.0;
// Smooth Period
period = 0.2 * newPeriod + 0.8 * p_period;
// Phase calculation
double phase = Math.Abs(i1) >= double.Epsilon ? Math.Atan(q1 / i1) * RadToDeg : 0.0;
// Adaptive alpha
double delta = Math.Max(p_phase - phase, 1.0);
double alpha = fastLimit / delta;
alpha = Math.Clamp(alpha, slowLimit, fastLimit);
// Final indicators
mama = alpha * priceBuffer[bufferIdx] + (1.0 - alpha) * p_mama;
// Update previous state
p_i2 = i2;
p_q2 = q2;
p_re = re;
p_im = im;
p_period = period;
p_phase = phase;
p_mama = mama;
}
else
{
// Initialization
sumPr += price;
double avg = count > 0 ? sumPr / count : price;
mama = avg;
// Init simple state
smoothBuffer[bufferIdx] = 0;
detrender[bufferIdx] = 0;
I1_buffer[bufferIdx] = 0;
Q1_buffer[bufferIdx] = 0;
// Set initial p_state
p_mama = avg;
p_period = 0; // Initial period state
p_phase = 0;
// Initialize other state variables if needed for next iteration logic?
// Actually they just stay 0/default until we hit count > 6
}
output[i] = mama;
}
}
public string Name { get; set; }
}
lib/trends/mama/Mama.md
+38
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@@ -62,6 +62,44 @@ MAMA is particularly valuable for identifying trends in markets with varying cyc
* **Mathematical complexity:** Requires proper implementation of digital signal processing concepts for accurate results
* **Complementary tools:** Works best when combined with momentum indicators or volume analysis for confirmation
## C# Implementation
### Standard Usage
```csharp
using QuanTAlib;
// Create MAMA with default parameters
var mama = new Mama(fastLimit: 0.5, slowLimit: 0.05);
// Update with new price
var result = mama.Update(new TValue(DateTime.UtcNow, 100.0));
Console.WriteLine($"MAMA: {result.Value}");
Console.WriteLine($"FAMA: {mama.Fama.Value}");
```
### Static API (High Performance)
```csharp
// Calculate MAMA for an entire array
double[] prices = { ... };
double[] results = new double[prices.Length];
Mama.Batch(prices, results, fastLimit: 0.5, slowLimit: 0.05);
```
### Event-Driven
```csharp
var source = new TSeries();
var mama = new Mama(source);
mama.Pub += (item) => {
Console.WriteLine($"MAMA: {item.Value}");
Console.WriteLine($"FAMA: {mama.Fama.Value}");
};
```
## References
1. Ehlers, J. (2001). *MESA and Trading Market Cycles*. John Wiley & Sons.